R version 2.6.1 (2007-11-26)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1.3,0,1.2,0,1.6,0,1.7,0,1.5,0,0.9,0,1.5,0,1.4,0,1.6,0,1.7,0,1.4,0,1.8,0,1.7,0,1.4,0,1.2,0,1.0,0,1.7,0,2.4,0,2.0,0,2.1,0,2.0,0,1.8,0,2.7,0,2.3,0,1.9,0,2.0,0,2.3,0,2.8,0,2.4,0,2.3,0,2.7,0,2.7,0,2.9,0,3.0,0,2.2,0,2.3,0,2.8,0,2.8,0,2.8,0,2.2,0,2.6,0,2.8,0,2.5,0,2.4,0,2.3,0,1.9,0,1.7,0,2.0,0,2.1,0,1.7,0,1.8,0,1.8,0,1.8,0,1.3,0,1.3,0,1.3,0,1.2,0,1.4,0,2.2,0,2.9,1),dim=c(2,60),dimnames=list(c('y','x'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('y','x'),1:60))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
y x
1 1.3 0
2 1.2 0
3 1.6 0
4 1.7 0
5 1.5 0
6 0.9 0
7 1.5 0
8 1.4 0
9 1.6 0
10 1.7 0
11 1.4 0
12 1.8 0
13 1.7 0
14 1.4 0
15 1.2 0
16 1.0 0
17 1.7 0
18 2.4 0
19 2.0 0
20 2.1 0
21 2.0 0
22 1.8 0
23 2.7 0
24 2.3 0
25 1.9 0
26 2.0 0
27 2.3 0
28 2.8 0
29 2.4 0
30 2.3 0
31 2.7 0
32 2.7 0
33 2.9 0
34 3.0 0
35 2.2 0
36 2.3 0
37 2.8 0
38 2.8 0
39 2.8 0
40 2.2 0
41 2.6 0
42 2.8 0
43 2.5 0
44 2.4 0
45 2.3 0
46 1.9 0
47 1.7 0
48 2.0 0
49 2.1 0
50 1.7 0
51 1.8 0
52 1.8 0
53 1.8 0
54 1.3 0
55 1.3 0
56 1.3 0
57 1.2 0
58 1.4 0
59 2.2 0
60 2.9 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
1.9678 0.9322
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.0678 -0.3928 -0.0339 0.3572 1.0322
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.96780 0.07091 27.749 <2e-16 ***
x 0.93220 0.54930 1.697 0.095 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.5447 on 58 degrees of freedom
Multiple R-Squared: 0.04731, Adjusted R-squared: 0.03088
F-statistic: 2.88 on 1 and 58 DF, p-value: 0.09504
> postscript(file="/var/www/html/rcomp/tmp/1g4ej1197487861.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2q35w1197487861.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3oaw81197487861.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4418l1197487861.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5v4aw1197487861.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 60
Frequency = 1
1 2 3 4 5
-6.677966e-01 -7.677966e-01 -3.677966e-01 -2.677966e-01 -4.677966e-01
6 7 8 9 10
-1.067797e+00 -4.677966e-01 -5.677966e-01 -3.677966e-01 -2.677966e-01
11 12 13 14 15
-5.677966e-01 -1.677966e-01 -2.677966e-01 -5.677966e-01 -7.677966e-01
16 17 18 19 20
-9.677966e-01 -2.677966e-01 4.322034e-01 3.220339e-02 1.322034e-01
21 22 23 24 25
3.220339e-02 -1.677966e-01 7.322034e-01 3.322034e-01 -6.779661e-02
26 27 28 29 30
3.220339e-02 3.322034e-01 8.322034e-01 4.322034e-01 3.322034e-01
31 32 33 34 35
7.322034e-01 7.322034e-01 9.322034e-01 1.032203e+00 2.322034e-01
36 37 38 39 40
3.322034e-01 8.322034e-01 8.322034e-01 8.322034e-01 2.322034e-01
41 42 43 44 45
6.322034e-01 8.322034e-01 5.322034e-01 4.322034e-01 3.322034e-01
46 47 48 49 50
-6.779661e-02 -2.677966e-01 3.220339e-02 1.322034e-01 -2.677966e-01
51 52 53 54 55
-1.677966e-01 -1.677966e-01 -1.677966e-01 -6.677966e-01 -6.677966e-01
56 57 58 59 60
-6.677966e-01 -7.677966e-01 -5.677966e-01 2.322034e-01 -6.505213e-17
> postscript(file="/var/www/html/rcomp/tmp/6vxf21197487861.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -6.677966e-01 NA
1 -7.677966e-01 -6.677966e-01
2 -3.677966e-01 -7.677966e-01
3 -2.677966e-01 -3.677966e-01
4 -4.677966e-01 -2.677966e-01
5 -1.067797e+00 -4.677966e-01
6 -4.677966e-01 -1.067797e+00
7 -5.677966e-01 -4.677966e-01
8 -3.677966e-01 -5.677966e-01
9 -2.677966e-01 -3.677966e-01
10 -5.677966e-01 -2.677966e-01
11 -1.677966e-01 -5.677966e-01
12 -2.677966e-01 -1.677966e-01
13 -5.677966e-01 -2.677966e-01
14 -7.677966e-01 -5.677966e-01
15 -9.677966e-01 -7.677966e-01
16 -2.677966e-01 -9.677966e-01
17 4.322034e-01 -2.677966e-01
18 3.220339e-02 4.322034e-01
19 1.322034e-01 3.220339e-02
20 3.220339e-02 1.322034e-01
21 -1.677966e-01 3.220339e-02
22 7.322034e-01 -1.677966e-01
23 3.322034e-01 7.322034e-01
24 -6.779661e-02 3.322034e-01
25 3.220339e-02 -6.779661e-02
26 3.322034e-01 3.220339e-02
27 8.322034e-01 3.322034e-01
28 4.322034e-01 8.322034e-01
29 3.322034e-01 4.322034e-01
30 7.322034e-01 3.322034e-01
31 7.322034e-01 7.322034e-01
32 9.322034e-01 7.322034e-01
33 1.032203e+00 9.322034e-01
34 2.322034e-01 1.032203e+00
35 3.322034e-01 2.322034e-01
36 8.322034e-01 3.322034e-01
37 8.322034e-01 8.322034e-01
38 8.322034e-01 8.322034e-01
39 2.322034e-01 8.322034e-01
40 6.322034e-01 2.322034e-01
41 8.322034e-01 6.322034e-01
42 5.322034e-01 8.322034e-01
43 4.322034e-01 5.322034e-01
44 3.322034e-01 4.322034e-01
45 -6.779661e-02 3.322034e-01
46 -2.677966e-01 -6.779661e-02
47 3.220339e-02 -2.677966e-01
48 1.322034e-01 3.220339e-02
49 -2.677966e-01 1.322034e-01
50 -1.677966e-01 -2.677966e-01
51 -1.677966e-01 -1.677966e-01
52 -1.677966e-01 -1.677966e-01
53 -6.677966e-01 -1.677966e-01
54 -6.677966e-01 -6.677966e-01
55 -6.677966e-01 -6.677966e-01
56 -7.677966e-01 -6.677966e-01
57 -5.677966e-01 -7.677966e-01
58 2.322034e-01 -5.677966e-01
59 -6.505213e-17 2.322034e-01
60 NA -6.505213e-17
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7.677966e-01 -0.66779661
[2,] -3.677966e-01 -0.76779661
[3,] -2.677966e-01 -0.36779661
[4,] -4.677966e-01 -0.26779661
[5,] -1.067797e+00 -0.46779661
[6,] -4.677966e-01 -1.06779661
[7,] -5.677966e-01 -0.46779661
[8,] -3.677966e-01 -0.56779661
[9,] -2.677966e-01 -0.36779661
[10,] -5.677966e-01 -0.26779661
[11,] -1.677966e-01 -0.56779661
[12,] -2.677966e-01 -0.16779661
[13,] -5.677966e-01 -0.26779661
[14,] -7.677966e-01 -0.56779661
[15,] -9.677966e-01 -0.76779661
[16,] -2.677966e-01 -0.96779661
[17,] 4.322034e-01 -0.26779661
[18,] 3.220339e-02 0.43220339
[19,] 1.322034e-01 0.03220339
[20,] 3.220339e-02 0.13220339
[21,] -1.677966e-01 0.03220339
[22,] 7.322034e-01 -0.16779661
[23,] 3.322034e-01 0.73220339
[24,] -6.779661e-02 0.33220339
[25,] 3.220339e-02 -0.06779661
[26,] 3.322034e-01 0.03220339
[27,] 8.322034e-01 0.33220339
[28,] 4.322034e-01 0.83220339
[29,] 3.322034e-01 0.43220339
[30,] 7.322034e-01 0.33220339
[31,] 7.322034e-01 0.73220339
[32,] 9.322034e-01 0.73220339
[33,] 1.032203e+00 0.93220339
[34,] 2.322034e-01 1.03220339
[35,] 3.322034e-01 0.23220339
[36,] 8.322034e-01 0.33220339
[37,] 8.322034e-01 0.83220339
[38,] 8.322034e-01 0.83220339
[39,] 2.322034e-01 0.83220339
[40,] 6.322034e-01 0.23220339
[41,] 8.322034e-01 0.63220339
[42,] 5.322034e-01 0.83220339
[43,] 4.322034e-01 0.53220339
[44,] 3.322034e-01 0.43220339
[45,] -6.779661e-02 0.33220339
[46,] -2.677966e-01 -0.06779661
[47,] 3.220339e-02 -0.26779661
[48,] 1.322034e-01 0.03220339
[49,] -2.677966e-01 0.13220339
[50,] -1.677966e-01 -0.26779661
[51,] -1.677966e-01 -0.16779661
[52,] -1.677966e-01 -0.16779661
[53,] -6.677966e-01 -0.16779661
[54,] -6.677966e-01 -0.66779661
[55,] -6.677966e-01 -0.66779661
[56,] -7.677966e-01 -0.66779661
[57,] -5.677966e-01 -0.76779661
[58,] 2.322034e-01 -0.56779661
[59,] -6.505213e-17 0.23220339
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7.677966e-01 -0.66779661
2 -3.677966e-01 -0.76779661
3 -2.677966e-01 -0.36779661
4 -4.677966e-01 -0.26779661
5 -1.067797e+00 -0.46779661
6 -4.677966e-01 -1.06779661
7 -5.677966e-01 -0.46779661
8 -3.677966e-01 -0.56779661
9 -2.677966e-01 -0.36779661
10 -5.677966e-01 -0.26779661
11 -1.677966e-01 -0.56779661
12 -2.677966e-01 -0.16779661
13 -5.677966e-01 -0.26779661
14 -7.677966e-01 -0.56779661
15 -9.677966e-01 -0.76779661
16 -2.677966e-01 -0.96779661
17 4.322034e-01 -0.26779661
18 3.220339e-02 0.43220339
19 1.322034e-01 0.03220339
20 3.220339e-02 0.13220339
21 -1.677966e-01 0.03220339
22 7.322034e-01 -0.16779661
23 3.322034e-01 0.73220339
24 -6.779661e-02 0.33220339
25 3.220339e-02 -0.06779661
26 3.322034e-01 0.03220339
27 8.322034e-01 0.33220339
28 4.322034e-01 0.83220339
29 3.322034e-01 0.43220339
30 7.322034e-01 0.33220339
31 7.322034e-01 0.73220339
32 9.322034e-01 0.73220339
33 1.032203e+00 0.93220339
34 2.322034e-01 1.03220339
35 3.322034e-01 0.23220339
36 8.322034e-01 0.33220339
37 8.322034e-01 0.83220339
38 8.322034e-01 0.83220339
39 2.322034e-01 0.83220339
40 6.322034e-01 0.23220339
41 8.322034e-01 0.63220339
42 5.322034e-01 0.83220339
43 4.322034e-01 0.53220339
44 3.322034e-01 0.43220339
45 -6.779661e-02 0.33220339
46 -2.677966e-01 -0.06779661
47 3.220339e-02 -0.26779661
48 1.322034e-01 0.03220339
49 -2.677966e-01 0.13220339
50 -1.677966e-01 -0.26779661
51 -1.677966e-01 -0.16779661
52 -1.677966e-01 -0.16779661
53 -6.677966e-01 -0.16779661
54 -6.677966e-01 -0.66779661
55 -6.677966e-01 -0.66779661
56 -7.677966e-01 -0.66779661
57 -5.677966e-01 -0.76779661
58 2.322034e-01 -0.56779661
59 -6.505213e-17 0.23220339
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7guo61197487862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/84zc41197487862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/93ya71197487862.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/10olrj1197487862.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11nwcf1197487862.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12c14x1197487862.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13amhf1197487862.tab")
>
> system("convert tmp/1g4ej1197487861.ps tmp/1g4ej1197487861.png")
> system("convert tmp/2q35w1197487861.ps tmp/2q35w1197487861.png")
> system("convert tmp/3oaw81197487861.ps tmp/3oaw81197487861.png")
> system("convert tmp/4418l1197487861.ps tmp/4418l1197487861.png")
> system("convert tmp/5v4aw1197487861.ps tmp/5v4aw1197487861.png")
> system("convert tmp/6vxf21197487861.ps tmp/6vxf21197487861.png")
> system("convert tmp/7guo61197487862.ps tmp/7guo61197487862.png")
> system("convert tmp/84zc41197487862.ps tmp/84zc41197487862.png")
> system("convert tmp/93ya71197487862.ps tmp/93ya71197487862.png")
>
>
> proc.time()
user system elapsed
3.949 2.454 4.270